qn_mg.hpp

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/*
 * SPDX-FileCopyrightText: Copyright (c) 2023-2024, NVIDIA CORPORATION.
 * SPDX-License-Identifier: Apache-2.0
 */
 
#include <cuml/common/logger.hpp>
#include <cuml/linear_model/qn.h>
 
#include <cumlprims/opg/matrix/data.hpp>
#include <cumlprims/opg/matrix/part_descriptor.hpp>
#include <raft/core/comms.hpp>
 
#include <cuda_runtime.h>
 
#include <vector>
using namespace MLCommon;
 
namespace ML {
namespace GLM {
namespace opg {
 
template <typename T>
std::vector<T> getUniquelabelsMG(const raft::handle_t& handle,
                                 Matrix::PartDescriptor& input_desc,
                                 std::vector<Matrix::Data<T>*>& labels);
 
template <typename T>
void qnFit(raft::handle_t& handle,
           std::vector<Matrix::Data<T>*>& input_data,
           Matrix::PartDescriptor& input_desc,
           std::vector<Matrix::Data<T>*>& labels,
           T* coef,
           const qn_params& pams,
           bool X_col_major,
           bool standardization,
           int n_classes,
           T* f,
           int* num_iters);
 
template <typename T, typename I>
void qnFitSparse(raft::handle_t& handle,
                 std::vector<Matrix::Data<T>*>& input_values,
                 I* input_cols,
                 I* input_row_ids,
                 I X_nnz,
                 Matrix::PartDescriptor& input_desc,
                 std::vector<Matrix::Data<T>*>& labels,
                 T* coef,
                 const qn_params& pams,
                 bool standardization,
                 int n_classes,
                 T* f,
                 int* num_iters);
 
};  // namespace opg
};  // namespace GLM
};  // namespace ML